Скачать или смотреть Optimising Low-Emissions Zone Geofencing Strategy using SUMO with Vehicle Co-Simulation

In order to tackle urban air quality challenges, several cities in the UK are starting to implement Low Emissions Zone (LEZ) and Ultra-Low Emissions Zone (ULEZ) concepts. These zones only accept the cleanest vehicles, but it is likely that the rules will become more stringent with time, eventually moving towards zero emission zones. Brighton & Hove Buses already operate a fleet of extended range hybrid buses and implement a geofenced LEZ in a part of the city that sees high bus traffic. Within this zone, the hybrid buses run in electric only mode and outside of the zone they can run in hybrid modes. The current zone is fixed for all routes and all conditions.

Using a detailed Ricardo VSIM (Vehicle Simulation) bus model co-simulated with SUMO (a traffic simulation), Ricardo has investigated the effects of different geofence zones on bus battery life and NOx emissions in the city. A Brighton & Hove city model including traffic lights, bus stops and traffic was created in SUMO. To create the traffic, SUMO’s “random trips” Python function was used. Ricardo developed a GUI App in MATLAB to provide fine control of the distribution of the randomly generated trips. This was used successfully to correlate simulated traffic levels with car-count data at several locations within the city.

The detailed model of the extended range hybrid bus was run within the SUMO environment to investigate how the bus responded to traffic and different geofence zones. The geofence zone was optimised with a Design-of-Experiments (DoE) to find the emissions versus battery life trade-off curves. This was repeated for different traffic levels and for both directions along a route. Compared to the baseline strategy, currently implemented in the city, Ricardo found significant improvements in emissions and/or battery life were possible with alternative, flexible geofence zones.